The latest in property testing and sublinear time algorithms

News for October 2019

Last month was a lean month, with only three papers: one on direct product testing, one on finding forbidden patterns in a sequence, and one (an update of a paper which we had missed in the Spring) on quantum distribution testing.

Direct sum testing – the general case, by Irit Dinur and Konstantin Golubev (ECCC). Say a function \(f\colon \prod_{i=1}^d [n_i] \to \mathbb{F}_2\) is a direct product if it can be factored as \(f(x_1,\dots,x_d)=\sum_{i=1}^d f_i(x_i)\), where \(f_i\colon [n_i]\to\mathbb{F}_2\).This paper provides a 4-query tester (i.e., a proximity oblivious tester (POT)) for the direct product property, reminiscent of (and relying on) the BLR linearity test: specifically, draw two subsets \(S,T\subseteq [d]\) and two inputs \(x,y\in \prod_{i=1}^d [n_i]\) u.a.r., and accept iff\(f(x)+f(x_Sy)+f(x_Ty)+f(x_{S\Delta T}y) = 0\,.\)The main theorem of the paper is to show that the probability that this simple test rejects is lower bounded (up to a constant factor) by the distance of \(f\) to direct-product-ness. (The authors also provide a different POT making \(d+1\) queries, but with a simpler analysis.)

Finding monotone patterns in sublinear time, by Omri Ben-Eliezer, Clément Canonne, Shoham Letzter, and Erik Waingarten (ECCC). Given a function \(f\colon [n]\to\mathbb{R}\), a monotone subsequence of size \(k\) is a \(k\)-tuple of indices \(i_1 < \dots <i_k\) such that \(f(i_j) < f(i_{j+1})\) for all \(j\). This work considers (non-adaptive) one-sided testing of monotone-subsequence-freeness, or, equivalently, the task of finding such a monotone subsequence in a function promised to contain many of them. (This, in particular, generalizes the problem of one-sided monotonicity testing, which is the case \(k=2\).) The main result is a full characterization of the query complexity of this question (for constant \(k\)): strange as the exponent may seem, \(\Theta_\varepsilon( (\log n)^{\lfloor \log_2 k\rfloor} )\) queries are necessary and sufficient. The proof relies on a structural dichotomy result, stating that any far-from-free sequence either contains “easy to find” increasing subsequences with increasing gaps between the elements, or has a specific hierarchical structure.

Quantum Closeness Testing: A Streaming Algorithm and Applications, by Nengkun Yu (arXiv). This paper is concerned with quantum distribution testing in the local model, which only allows a very restricted (albeit, as the author argues, more natural and easier to implement) type of measurements, and is particularly well-suited to a streaming setting. The main contribution of this paper is to show a connection to classical distribution testing, allowing one to obtain quantum distribution testing upper bounds from their classical distribution testing counterparts. In more detail, the paper shows that, from local measurements to two \(d\)-dimensional quantum states \(\rho,\sigma\), one can provide access to two classical distributions \(p,q\) on \(\approx d^2\) elements such that (i) \(\| p-q\|_2 \approx \|\rho-\sigma\|_2/d\) and (ii) \(\| p\|_2,\| q\|_2 = O(1/d)\).Using this connection, the paper proceeds to establish a variety of upper bounds for testing several distribution properties in the local quantum model.